This paper presents a novel method for face description with single sample by adaptively weighted extended local binary pattern(AWELBP).The proposed algorithm utilizes an extended local binary pattern(ELBP) to represent faces partitioned into sub-patterns.Especially,in order to perform matching in the sense of the richness of identity information and to handle the partial occlusion problem,the proposed algorithm employs an adaptively weighting map to weight the sub-ELBP(SELBP) extracted from local areas based on the contribution of each sub-pattern to the final similarity measurement.Simulated experiments and comparisons on a subset of Yale face databases,a subset of Yale B face databases and ORL face databases under ideal condition,different illumination condition,different facial expression and partial occlusion show that the proposed algorithm is an outstanding method for single sample face recognition.